The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy

Abstract

Checkpoint inhibitor-based immunotherapies that target cytotoxic T lymphocyte antigen 4 (CTLA4) or the programmed cell death 1 (PD1) pathway have achieved impressive success in the treatment of different cancer types. Yet, only a subset of patients derive clinical benefit. It is thus critical to understand the determinants driving response, resistance and adverse effects. In this Review, we discuss recent work demonstrating that immune checkpoint inhibitor efficacy is affected by a combination of factors involving tumour genomics, host germline genetics, PD1 ligand 1 (PDL1) levels and other features of the tumour microenvironment, as well as the gut microbiome. We focus on recently identified molecular and cellular determinants of response. A better understanding of how these variables cooperate to affect tumour-host interactions is needed to optimize the implementation of precision immunotherapy.

Figures

Fig. 1 |. Immune checkpoint blockade and somatic mutations.

a | T cells recognize and become activated against peptide antigens through ligation of T cell surface receptors. Two signals are required for T cell activation. Signal 1 is generated by the binding of major histocompatibility complex (MHC)-presented immunogenic peptide antigen to the heterodimeric T cell receptor (TCR). Signal 2, also referred to as co-stimulation, is transduced via ligation of the T cell co-stimulatory surface receptor CD28 to its ligand CD80 (also known as B7–1) or CD86 (also known as B7–2) on the surface of professional antigen-presenting cells (APCs). Once activated, T cells begin to express co-inhibitory cell surface receptors, such as cytotoxic T lymphocyte antigen 4 (CTLA4) and programmed cell death 1 (PD1). Like CD28, CTLA4 binds CD80 and CD86, but with significantly higher affinity. CTLA4 ligation with CD80 or CD86 blocks co-stimulation (signal 2) and prevents continued T cell activation. Blockade of the CTLA4–CD80 or CTLA4–CD86 interaction therefore promotes activation of T cells in secondary lymphoid organs. Binding of PD1 to its ligand, PD1 ligand 1 (PDL1), inhibits signalling downstream of the TCR, thereby blocking signal 1. PDL1 is frequently expressed on tumours or in the tumour microenvironment. Therefore, PD1-targeted or PDL1-targeted antibody therapeutics can reinvigorate exhausted T cells at the tumour site. b | In tumours, mutated or aberrantly expressed proteins are processed via the immunoproteasome into peptides. These peptides can be loaded onto MHC class I (MHC I) molecules depending on the identity of their anchor residues (often positions 2 and 9). MHC-I-presented mutant peptides may or may not elicit a CD8+ T cell response depending on a number of factors including peptide sequence, TCR sequences and immune infiltration. A high mutation burden increases the chances of generating MHC-presented immunogenic neoepitopes. c | Both peptide immunogenicity and intratumoural clonal heterogeneity influence tumour immune responses.

Fig. 2 |. Multiple sources of diversity converge to influence tumour immunity.

The immunological synapse, consisting of a major histocompatibility complex (MHC)-presented peptide and a cognate T cell receptor (TCR), is the lynchpin of adaptive tumour immunity. Accurate predictions regarding this critical ternary complex could translate into predictions of immune checkpoint inhibitor (ICI) efficacy; however, each contributing element is characterized by vast evolutionarily sculpted diversity, rendering predictions challenging. Many current predictive algorithms consider only peptide–MHC binding. Multivariable models incorporating peptide processing, human leukocyte antigen (HLA) genotype and TCR repertoire analysis will be critical for improving predictions of tumour immunity and ICI response. a | Immunogenic neoepitopes can arise from non-synonymous single nucleotide variants (nsSNVs), small insertion or deletion (indel) mutations resulting in frameshifts or epigenetic reprogramming that allows aberrant expression of genes normally restricted to trophoblasts or early phases of development. Each process generates peptides that are foreign to the immune system; however, the fraction of amino acids per peptide that appears foreign to the immune system will differ. An nsSNV at a non-anchor, that is, non-MHC-binding, residue will generate a peptide that differs by only a single residue from a wild-type peptide previously presented to the immune system during thymic selection. As such, it is possible that an individual may have previously developed tolerance for neoepitopes generated in this manner. Alternatively, if an nsSNV generates a novel MHC-binding site, it is likely that the immune system has never been exposed to any part of the resultant MHC-presented peptide and that tolerance has not been developed. The same is true for neoepitopes generated via indel-induced frameshifts and epigenetic reprogramming. b | The HLA genes are among the most polymorphic in the human genome. There are thousands of known HLAA, HLAB and HLAC alleles. Each individual possesses two alleles of each HLA gene, resulting in vast inter-individual diversity in the ability to present tumour-derived neoepitopes. (Note that the HLA allelic combination estimate does not take into account lineage disequilibrium, which may reduce the total possible combinations empirically observed.) c | TCRs recognize and bind HLA-presented peptide epitopes. Every individual possesses a unique TCR repertoire generated via the semi-random recombination of variable (V), diversity (D) and joining (J) gene segments within every developing T cell of the body. TCR diversity is further multiplied by the deletion or insertion of nucleotides at gene segment junctions through the activity of terminal deoxynucleotide transferase. T cell clones subsequently undergo positive and negative thymic selection to enrich for T cells that bind self-MHC molecules but do not bind self-peptides. It is thought that both HLA and TCR genes have evolved to bind pathogen-derived sequences. This may influence which tumour-derived neoepitopes are most likely to elicit a productive T cell response. APC, antigen-presenting cell.